TY - GEN
T1 - EM clustering algorithm for automatic text summarization
AU - Ledeneva, Yulia
AU - Hernández, René García
AU - Soto, Romyna Montiel
AU - Reyes, Rafael Cruz
AU - Gelbukh, Alexander
PY - 2011
Y1 - 2011
N2 - Automatic text summarization has emerged as a technique for accessing only to useful information. In order to known the quality of the automatic summaries produced by a system, in DUC 2002 (Document Understanding Conference) has developed a standard human summaries called gold collection of 567 documents of single news. In this conference only five systems could outperforms the baseline heuristic in single extractive summarization task. So far, some approaches have got good results combining different strategies with language-dependent knowledge. In this paper, we present a competitive method based on an EM clustering algorithm for improving the quality of the automatic summaries using practically non language-dependent knowledge. Also, a comparison of this method with three text models is presented.
AB - Automatic text summarization has emerged as a technique for accessing only to useful information. In order to known the quality of the automatic summaries produced by a system, in DUC 2002 (Document Understanding Conference) has developed a standard human summaries called gold collection of 567 documents of single news. In this conference only five systems could outperforms the baseline heuristic in single extractive summarization task. So far, some approaches have got good results combining different strategies with language-dependent knowledge. In this paper, we present a competitive method based on an EM clustering algorithm for improving the quality of the automatic summaries using practically non language-dependent knowledge. Also, a comparison of this method with three text models is presented.
KW - Automatic text summarization
KW - EM clustering algorithm
KW - extractive summarization
KW - maximal frequent sequences
KW - n-grams
KW - text models
UR - http://www.scopus.com/inward/record.url?scp=82555164875&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-25324-9_26
DO - 10.1007/978-3-642-25324-9_26
M3 - Contribución a la conferencia
SN - 9783642253232
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 305
EP - 315
BT - Advances in Artificial Intelligence - 10th Mexican International Conference on Artificial Intelligence, MICAI 2011, Proceedings
T2 - 10th Mexican International Conference on Artificial Intelligence, MICAI 2011
Y2 - 26 November 2011 through 4 December 2011
ER -